If your company is looking forward to implement automated process in order to improve its business performance, the upcoming Test Data Management (TDM) needs must be considered as a very strategic business decision. It is not enough to set up automated test data collection and analysis; you should also consider and integrate it with other business areas such as accounting, human resources, supply chain, and so on. With this, you will be able to achieve greater operational efficiency and productivity. Likewise, TDM can bring significant business benefits to your business. Below you will enjoy:

4 Keys for Better Test Data Management: This week s article looks at synthetic test data generation from the viewpoint of greater testing rigor. The following week will end the series by looking further at how tDM improves testing agility. Hopefully, this discussion has stimulated your thinking about this important automation tool.

Test Data Management with EDI or Data Visualization Tools like Ketera and Agresso are great ways of managing large amounts of data via standard business applications. They allow data to be accessed in various formats like Excel, CSV, and RTF. Another advantage of using these tools is that it helps to create user interfaces which look familiar to IT employees. They can also save money on data-intensive tasks because of the decreased time spent on installation, configuration, and training.

Using Test Data Automation tools will help you to reduce unnecessary testing time, provide a more consistent data collection, and increase test coverage. In addition, data automation makes it easier to supervise the testing team and make sure that they are completing all the tasks necessary to meet business objectives. As an entrepreneur, you want to maximize all of the available resources for increasing business productivity, profitability, and customer satisfaction. So, you should always put testing as a priority.

Data automation should be used carefully. For instance, when a large amount of data is to be processed, sometimes it is best to outsource the entire process to reduce operational costs. However, there are situations where data collection must be done manually to ensure accuracy and consistency. For instance, there might be some combination of web services and mobile services involved in an organization's consumer experience and business operations. In these cases, data collection will have to be performed by the professionals, rather than relying on "cheap" outsourced teams.

The aim of using test data automation tools should be to automate as much as possible. This goal is easily achieved by using primary and secondary processing technologies. These technologies will allow you to filter, group, and summarize data. Also, you can perform transformations like column or row replacement. Some of the common combinations include: